Computational Modeling of the Photophysics of Organic Molecules and Materials

有机分子和材料光物理学的计算模型

• 批准号: 0719350
• 负责人: David Yaron
• 金额: $ 29.66万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-01 至 2011-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0719350&HistoricalAwards=false
• 关键词: Computational; Modeling; Photophysics; Organic; Molecules

David J. Yaron of Carnegie-Melon University is supported by the Theoretical and Computational Chemistry Program to develop a reliable, quantum chemistry approach to the excited electronic states of organic molecules and materials, and to use this approach to model important photophysical processes. The PI is using techniques that greatly expand the range of questions that can be investigated with quantum chemistry. These include a model for including dielectric electron-hole screening, an effective particle approach, and schemes to include the effects of disorder. Implementation of these methods is within the INDO (Intermediate Neglect of Differential Overlap) semi-empirical model. The methods are being extended to more sophisticated quantum chemical models to obtain better descriptions of properties that rely on excited state potential energy surfaces. This work is having a broad impact in improving our understanding the fundamental photophysical processes that underlie electronic applications such as sensors, flat-screen displays, and photocells. Educational outreach is underway through scenario-based learning activities for introductory chemistry courses. These activities are based closely on the PI''s research, and are developed and disseminated in collaboration with the ChemCollective headed by the PI.

卡内基-梅隆大学的 David J. Yaron 在理论和计算化学项目的支持下，开发了一种可靠的量子化学方法来研究有机分子和材料的激发电子态，并使用这种方法来模拟重要的光物理过程。 PI 正在使用的技术大大扩展了量子化学可以研究的问题范围。 其中包括包含电介质电子空穴屏蔽的模型、有效的粒子方法以及包含无序影响的方案。 这些方法的实施是在 INDO（中间忽略微分重叠）半经验模型内进行的。 这些方法正在扩展到更复杂的量子化学模型，以获得依赖于激发态势能表面的性质的更好描述。 这项工作对提高我们对传感器、平板显示器和光电管等电子应用基础光物理过程的理解产生了广泛的影响。 正在通过针对化学入门课程的基于情景的学习活动开展教育推广。 这些活动紧密基于 PI 的研究，并与 PI 领导的 ChemCollective 合作开发和传播。